Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges -

Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

8th International Workshop, STACOM 2017, Held in Conjunction with MICCAI 2017, Quebec City, Canada, September 10-14, 2017, Revised Selected Papers
Buch | Softcover
XIII, 260 Seiten
2018 | 1st ed. 2018
Springer International Publishing (Verlag)
978-3-319-75540-3 (ISBN)
53,49 inkl. MwSt
This book constitutes the thoroughly refereed post-workshop proceedings of the 8th International Workshop on Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges 2017, held in conjunction with MICCAI 2017, in Quebec, Canada, in September 2017. The 27 revised full workshop papers were carefully reviewed and selected from 35 submissions. The papers cover a wide range of topics computational imaging and modelling of the heart, as well as statistical cardiac atlases. The topics of the workshop included: cardiac imaging and image processing, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods. Besides regular contributing papers, additional efforts of STACOM workshop were also focused on two challenges: ACDC and MM-WHS.
Erscheinungsdatum
Reihe/Serie Image Processing, Computer Vision, Pattern Recognition, and Graphics
Lecture Notes in Computer Science
Zusatzinfo XIII, 260 p. 94 illus.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 423 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Applications • Artificial Intelligence • Computer Science • conference proceedings • Cross-validation • Image Processing • Image Segmentation • Informatics • machine learning • Neural networks • Research • segmentation methods • Support Vector Machines SVM
ISBN-10 3-319-75540-4 / 3319755404
ISBN-13 978-3-319-75540-3 / 9783319755403
Zustand Neuware
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